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Robust line tracking using a particle filter for camera pose estimation

Published: 01 November 2006 Publication History

Abstract

This paper presents a robust line tracking approach for camera pose estimation which is based on particle filtering framework. Particle filters are sequential Monte Carlo methods based on point mass (or "particle") representations of probability densities, which can be applied to any state-space model. Their ability to deal with non-linearities and non-Gaussian statistics allows to improve robustness comparing to existing approaches, such as those based on the Kalman filter. We propose to use the particle filter to compute the posterior density for the camera 3D motion parameters. The experimental results indicate the effectiveness of our approach and demonstrate its robustness even when dealing with severe occlusion.

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    cover image ACM Conferences
    VRST '06: Proceedings of the ACM symposium on Virtual reality software and technology
    November 2006
    400 pages
    ISBN:1595933212
    DOI:10.1145/1180495
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    Published: 01 November 2006

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    Author Tags

    1. 3D pose estimation
    2. augmented reality
    3. line tracking
    4. particle filter

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    • (2016)Adaptive dynamic time warping for recognition of natural gestures2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)10.1109/IPTA.2016.7820971(1-6)Online publication date: Dec-2016
    • (2016)Sliding Movement Platform for Mixed Reality ApplicationIFAC-PapersOnLine10.1016/j.ifacol.2016.10.67649:21(662-667)Online publication date: 2016
    • (2016)Combination of HMM and DTW for 3D Dynamic Gesture Recognition Using Depth OnlyInformatics in Control, Automation and Robotics 12th International Conference, ICINCO 2015 Colmar, France, July 21-23, 2015 Revised Selected Papers10.1007/978-3-319-31898-1_13(229-245)Online publication date: 15-May-2016
    • (2016)A Non-rigid Face Tracking Method for Wide Rotation Using Synthetic DataPattern Recognition: Applications and Methods10.1007/978-3-319-27677-9_12(185-198)Online publication date: 9-Jan-2016
    • (2015)U3PT: A New Dataset for Unconstrained 3D Pose Tracking EvaluationComputer Analysis of Images and Patterns10.1007/978-3-319-23192-1_54(642-653)Online publication date: 25-Aug-2015
    • (2013)3D Camera Tracking for Mixed Reality using Multi-Sensors TechnologyGeographic Information Systems10.4018/978-1-4666-2038-4.ch128(2164-2175)Online publication date: 2013
    • (2012)3D Camera Tracking for Mixed Reality using Multi-Sensors TechnologyDepth Map and 3D Imaging Applications10.4018/978-1-61350-326-3.ch027(528-539)Online publication date: 2012
    • (2011)Efficient initialization schemes for real-time 3D camera tracking using image sequences2011 11th International Conference on Intelligent Systems Design and Applications10.1109/ISDA.2011.6121745(743-747)Online publication date: Nov-2011
    • (2010)Real-time camera tracking for structured environment using an iterated particle filter2010 IEEE International Conference on Systems, Man and Cybernetics10.1109/ICSMC.2010.5641678(3039-3044)Online publication date: Oct-2010
    • (2009)A hand-held 3D display system that facilitates direct manipulation of 3D virtual objectsProceedings of the 8th International Conference on Virtual Reality Continuum and its Applications in Industry10.1145/1670252.1670268(65-70)Online publication date: 14-Dec-2009
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